In the upcoming year, there will be new technology that can deliver better and faster data insights, new uses for older BI tools, and a shift in analytics strategy for data crunchers everywhere.

Do you want to find out what’s new, developing, and old hat in the business intelligence world? Take a look at the five business intelligence trends for 2018 that we’ve highlighted below.

1. Augmented Analytics

Imagine being able to submit a verbal query to your data analytics software and not just get pertinent data back, but valuable, strategy-changing recommendations. Augmented analytics is the combination of several data processes that could ultimately provide you with a simple, actionable, data-driven answer.

In fact, augmented analytics is a “particularly strategic growing area that uses machine learning for automating data preparation, insight discovery and insight sharing for a broad range of business users, operational workers, and citizen data scientists” (David Cleary, Gartner’s VP).

Augmented analytics gives your analytics team the gift of time. Traditionally resource-draining and time-intensive analyses can be significantly reduced by using machine-learning and natural-language processing mediated analytics. If you want to remain competitive, you’ll need to leverage your data quicker than your competitors, and augmented analytics is going to be the tool you need to do this.

2. Artificial Intelligence

Artificial Intelligence (AI) has been around for a while now and has recently become a buzzword that people throw around during business meetings. For business intelligence, AI means a series of narrowly defined computer processes that help augment data with a specific task in mind. Somewhat erroneously associated with robots, AI provides a learning machine that thinks (hopefully) like a human, which helps unravel some business data mysteries.

“A recent Gartner survey showed that 59% of organizations are still gathering information to build their AI strategies, while the remainder have already made progress in piloting or adopting AI solutions”, says Gartner’s Cleary.

3. Cloud Business Intelligence

Using the cloud has been a source of worry for business intelligence experts for years, considering the potential cybersecurity risks that off-site cloud storage poses. The good news is that we’ll see some modifications to the typical cloud architectures in 2018 that will lead to fewer cybersecurity risks by providing data storage that is both on and off-site. You’ll get to pick which data you put into the cloud, and which proprietary or sensitive data you want to keep on your company’s servers.

An added bonus to implementing cloud data storage is the increase in speed, scalability, and flexibility. With the cloud becoming a more feasible method of storing large, proprietary data sets, business intelligence experts will be able to provide shrewd business strategies at a faster rate.

This year we will see a wide-spread adoption of hybrid cloud architectures which deliver the best of both worlds: some data in the cloud, and some housed right in your on-site servers. This allows you to keep your proprietary data in-house, while giving you the ability to use the cloud for your mundane data tasks at the same time.

4. More Data Visualization Features

Data Visualizations are depictions of information that summarize and explain complex data to a targeted audience. Many people can make data look good, few can tell you what data means. Fewer still can craft clear and concise visualizations that convey the correct message from their data.

Johnny Lee, principal and forensic technology national practice leader at Grant Thornton LLP, says:

“What I see often are people trained on visualization tools, not analysis. What that begets is an unwarranted trust in the underlying data, and [the] belief that the only ‘analysis’ required for such data is to beautify it.”

In 2018, more and more business tools are going to provide data visualizations. Why? Discerning business owners want easy insight into their data. Don’t let the presence of a data visualizations feature fool you. Pretty charts and graphs can’t stand in for shrewd analysis of the hard data. All that being said, not all data visualizations are bad.

At a recent lecture, Edward Tufte, professor emeritus at Yale University and a pioneer in the field of data visualization, summed up the way to create a good data visualization: “Do whatever it takes to get your message across.” That means steer clear of ho-hum bar charts, line graphs, and the evil pie chart in lieu of creating visuals that not only convey the right message to your audience but allow them to interact with you as well.For BI software users, it will be important to look at what the graphs and charts are really telling you about your data. Don’t be fooled by a pretty picture.

5. Modern and Accessible business intelligence

When you think of business intelligence, do you envision a bunch of data scientists, SQL experts, and systems analysts sitting in their cubicles beating the data into submission? Throw that visualization out of your head completely in 2018 (and beyond) as business intelligence becomes highly automated and therefore more easily used by citizen data scientistsModern business intelligence means less specialization, more automation, and a free-for-all approach to data analytics overall.

Modern business intelligence will create streamlined automated processes for getting at the gut of business data. This means an increase in productivity and subsequently, growth in the number of actions related to the data.

“Making data science products easier for citizen data scientists to use will increase vendors’ reach across the enterprise as well as help overcome the skills gap”

says Alexander Linden, research vice president at Gartner.

“The key to simplicity is the automation of tasks that are repetitive, manually intensive and don’t require deep data science expertise.”

Gartner predicts that 40% of data science tasks will be automated by 2020, and in 2018 you can expect to see the start of this trend. Is the revered data scientist job title going out of style with modern business intelligence? Probably not by 2018. But, according to Linden, by 2020 “fewer data scientists will be needed to do the same amount of work, but every advanced data science project will still require at least one or two data scientists”.Data scientists better sharpen up other skills on their resume to stay relevant.

6. Self-service BI

Self-service BI is when a staff member uses a BI solution to analyze live business data and build immediate, accurate, and customized visual reports without the need for clunky reports from IT specialists. Gartner predicts that by the end of the year, most decision makers and business users will have access to self-service BI solutions to make better-informed decisions, and act on them more quickly. According to Gartner research vice president, Rita Sallam:

“self-service data integration will reduce the significant time and complexity users face in preparing their data for analysis and shift much of the activity from IT to the business user.”

7. Mobile BI

In today’s fast-paced business environment, decision makers across a business require access to critical information anywhere, anytime. This has largely been made easier with BI’s increased accessibility on mobile and the improving ability of smartphones to allow more detailed information to be analyzed on a mobile device. This has invariably led to the rise of mobile business intelligence (mobile BI).

The number of businesses using mobile BI has grown significantly year-on-year. According to the Aberdeen Group, companies using mobile BI are 68% percent more likely to get business data on time than companies not using it. This means that in a cutthroat business environment, companies that use mobile BI are in a significantly better position. Using data-driven decision making, they have the best chance of staying ahead of the competition.

It looks like 2018 will turn out to be a year full of business intelligence innovations and further refinement of some previously existing technologies…

Thanks to: capterra, technologyadvice

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